Big Data and Big Data Analytics Explained

by Garry S.

What is “Big Data” and What Should You Know About it?

If you have heard the term Big Data quite often and are wondering what it is all about, this article will clear your doubts. These are huge sets of data, which are analyzed through computers to discover certain trends and patterns about a specific aspect of that data. There is no specification on how vast or little this data can be to be referred to as Big Data if that is sufficient to draw good conclusions or inferences.

The fact is that the term Big Data describes both structured, as well as unstructured data sets that are so huge to process via traditional methodologies.

At the same time, Big Data is a new concept, which represents the varied data types and the growing data being collected. With the lion's share of the global information becoming digitized and moving online. It also signifies that analysts can start using them as data. Today, videos, music, online, books, and social networking sites among others have led to the massive growth in data, which can be used for analysis.

Today, anything and everything that is done by any online user is saved, as well as, tracked as data. For instance, when you use your Kindle to read a book, the device creates data about the content you have been reading, the speed of your reading, your time of reading and so on. Likewise, when you listen to music, data is generated about the songs that you listen frequently and in what sequence you listen. Plus, when you own a smartphone, it keeps uploading data about how quickly you have been moving, the kind of apps being used by you, and your location.

Accessing Big Data

There is an unlimited number of locations where you can avail Big Data, and these places are simply increasing with the passage of time. When you search using Google, you can find data repositories of endless types. Rather, the tragedy is even today; many people are unaware of the volume of data, which exist for analysis and access already.

The way one can access, as well as, utilize the data can be categorized into six different parts.

1. Data extractionThe first step before anything else can be done the availability of data. It can be done in various ways and typically through an Application Programming Interface to the web service of a company.

2. Data storageThe storage factor is the top issue with Big Data. The key determinants are the expertise, as well as, the budget of a person whose responsibility is to set up data storage since a majority of the providers need some kind of programming expertise to implement.

3. Data cleaningData sets are available in some shapes and sizes. Before even contemplating the way data storage will happen, make sure that its format is acceptable and neat.

4. Data miningIt is a technique to discover valuable insights about a database. The key goal is to offer meaningful predictions so that decisions can be made by data being held currently.

5. Data analysisAfter the data collection is over, it should now be analyzed to reveal exciting trends and patterns. Seasoned data analysts have the skill and the expertise to detect something interesting or a conclusion that is yet to be revealed by someone else.

6. Data visualizationIt is in all probability the most crucial stage. It is that stage when all the jobs done earlier are taken as input and returns a visualization as an output, which can be understood by anyone.

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